Safe RLHF separates helpfulness and harmlessness preferences into distinct models and uses Lagrangian constrained optimization to improve both during LLM fine-tuning.
Among the four types listed above, the first type can be regarded as an intermediate state achieved while simultaneously enhancing the model’s helpfulness and harmlessness
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Safe RLHF: Safe Reinforcement Learning from Human Feedback
Safe RLHF separates helpfulness and harmlessness preferences into distinct models and uses Lagrangian constrained optimization to improve both during LLM fine-tuning.